Prompts, our Enterprise tool for evaluating and refining LLM prompts, now supports multi-class text classification projects. This will enable you to label your text with more than one choice, allowing for more complex classification use cases.
This also means that projects with the choice="multiple"
parameter set will now appear in the Target Project drop-down menu when creating a Prompt (assuming that the project meets all other eligibility criteria).
You can now apply labels to video frames. Previously, we only supported per-video classification.
This new feature allows you to apply labels at a per-frame level. You can implement this feature using a new tag: <TimelineLabels>
.
For more information, see New! Video Frame Classification.
You can now select NER projects when creating a prompt. Previously, Prompts only supported Text Classification projects.
For more information, see Named entity recognition (NER) in our Prompts documentation.
You can now add JavaScript to your Label Studio projects to further customize your labeling experience.
Note that due to security precautions, custom scripts must be enabled for your organization before will see the Scripts option when configuring the labeling interface. Contact your account representative to request this feature.
For more information, see the following resources:
You can now use Azure OpenAI when creating Prompts. For more information, see Model provider API keys.
After:
created_by
was null.created_by
was null.The Prompts tool leverages ChatGPT to help you evaluate and refine your LLM prompts. You can also use Prompts to generate predictions for automating your labeling process, and to quickly bootstrap labeling projects.
For more information, see Automate Data Labeling with HumanSignal and our Prompts documentation.
The Label Studio UI has been upgraded with updated colors and fonts, giving it a sleek new look while maintaining the same intuitive navigation you're familiar with. All Label Studio tools, features, and settings are still in the same place, ensuring a smooth transition.
Improved performance on the Projects list page due to improvement on the API level.
Fixed an issue with Google Cloud Storage when the connection has the Use pre-signed URLs option disabled. In these situations, Google was sending pre-signed URLs with the format https://storage.googleapis.com
rather than sending BLOBs.
With this fix, Google Cloud Storage will begin returning BLOBs/base64 encoded data when Use pre-signed URLs is off. This means that Label Studio will start reading data from Google Cloud Storage buckets, which can result in large amounts of data being sent to your Label Studio instance - potentially affecting performance.
When using the annotator performance report, you can now filter by project or workspace.
HIDE_STORAGE_SETTINGS_FOR_MANAGER
environment variable set to True
, Managers will now be able to sync data from external storage as necessary rather than request assistance from an Admin user.
There is a new setting that can restrict users from uploading data directly to Label Studio, forcing them to only use cloud storage. If you would like to enable this setting, set the DISABLE_PROJECT_IMPORTS
environment variable to True
.
LABEL_STUDIO_
appearing in context logs.DEBUG
. The default log level is now INFO
.